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@@ -5,19 +5,19 @@ BreezySLAM
<p><p><p>
<b>Simple, efficient, open-source package for Simultaneous Localization and Mapping in Python and C++</b>
<a href="https://github.com/simondlevy/BreezySLAM">This repository</a> contains everything you need to
start working with
<a href="http://en.wikipedia.org/wiki/Lidar">Lidar</a>
-based
<a href="http://en.wikipedia.org/wiki/Simultaneous_localization_and_mapping">SLAM</a>
in Python or C++. There is also support for Matlab and Java, though I am no longer maintaining that
code.) BreezySLAM works with Python 2 and 3 on Linux and
Mac OS X, and with C++ on Linux and Windows. By using Python C extensions, we
were able to get the Python version to run as fast as C++. For maximum effiency
on 32-bit platforms, we use Streaming SIMD extensions (Intel) and NEON (ARMv7)
in the compute-intensive part of the code.
in Python. (There is also support for Matlab, C++, and Java; however, because of the popularity of
Python for this kind of work, I am no longer updating that code.)
BreezySLAM works with Python 2 and 3 on Linux and Mac OS X, and
with C++ on Linux and Windows.
By using Python C extensions, we were able to get the Python and Matlab versions to run
as fast as C++. For maximum effiency on 32-bit platforms, we use Streaming
SIMD extensions (Intel) and NEON (ARMv7) in the compute-intensive part
of the code.
</p><p>
BreezySLAM was inspired by the <a href="http://home.wlu.edu/%7Elambertk/#Software">Breezy</a>
approach to Graphical User Interfaces developed by my colleague
@@ -120,6 +120,27 @@ To try it out, you'll also need the <a href="https://github.com/simondlevy/xvlid
Python package. Once you've installed
both packages, you can run the <b>xvslam.py</b> example in the <b>BreezySLAM/examples</b> folder.
</p><h3>Installing for Matlab</h3>
<p>
I have run BreezySLAM in Matlab on 64-bit Windows, Linux, and Mac OS X. The <b>matlab</b> directory contains all the code you
need, including pre-compiled binaries for all three operating systems. To try it out in Matlab, add this directory to your
path, then change to the <b>examples</b> directory and do
<pre>
>> logdemo('exp2', 1)
</pre>
If you modify the source code or want to build the binary for a different OS, you can change to the <b>matlab</b>
directory and do
<pre>
>> make
</pre>
For making the binary on Windows I found
<a href="http://www.mathworks.com/matlabcentral/answers/95039-why-does-the-sdk-7-1-installation-fail-with-an-installation-failed-message-on-my-windows-system">these instructions</a> very helpful when I ran into trouble.
<h3>Installing for C++</h3>
Just cd to <tt><b>BreezySLAM/cpp</b></tt>, and do
@@ -147,6 +168,21 @@ the Makefile in this directory as well, if you don't use <tt><b>/usr/local/lib</
</p><p>
<h3>Installing for Java</h3>
In <tt><b>BreezySLAM/java/edu/wlu/cs/levy/breezyslam/algorithms</b></tt> and
<tt><b>BreezySLAM/java/edu/wlu/cs/levy/breezyslam/components</b></tt>,
edit the <tt>JDKINC</tt> variable in the Makefile to reflect where you installed the JDK.
Then run <b>make</b> in these directories.
<p>
For a quick demo, you can then cd to <tt><b>BreezySLAM/examples</b></tt> and do
<pre>
make javatest
</pre>
<h3>Notes on Windows installation</h3>